The struggle to diversify rural livelihoods: Bio-enterprise development initiatives and their impacts on agro-/pastoral communities in the drylands of Kenya

This article analyses the impacts of four different bio-enterprise initiatives on agro-pastoral livelihoods and on improved natural resources management (NRM) in the drylands of Kenya. In this way it contributes to an area of rural development that is gaining increasing interest, but still has little empirical evidence. Data were collected through interviews, focus group discussions, informal discussions and the study of reports. One of the key findings of this article is that diversification into enterprises requires cooperation among the stakeholders with their varying experiences in development, NRM and business development. In addition to initial investments, such enterprises need sustained financial, as well as other support like capacity development to survive the market introduction phase. For such enterprises to defend their market niches, the quantity and quality of the product are critical. In addition to support in human, financial, social, physical and natural capital, mentoring is another crucial factor for success.

Understanding heterogeneity in post-implementation enterprise system usage: towards a fit/misfit-experience-outcome typology

The overarching objective of this dissertation is to uncover why and how individually experienced fits and misfits translate into different outcomes of user behavior and satisfaction and whether these individual fit/misfit outcomes are in line with organizational intent. In search of patterns and possible archetype users in the context of ES PIPs, this dissertation is the first study that specifically links the theoretical concepts of the aggregated individual fit experiences with the individual and organizational outcome of these experiences (i.e. behavioral reaction, user satisfaction, and alignment with organizational intent). The case study’s findings provide preliminary support for four archetype users characterized by specific fit/misfit experience-outcome patterns.

Directional statistics: introduction

In many of the natural and physical sciences, measurements are directions, either in two or three dimensions. The analysis of directional data relies on specific statistical models and procedures, which differ from the usual models and methodologies of Cartesian data. This chapter briefly introduces statistical models and inference for this type of data. The basic von Mises-Fisher distribution is introduced and nonparametric methods such as goodness-of-fit tests are presented. Further references are given for exploring related topics such as correlation and regression.